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论文编号：	15788
作者编号：	2320234102
上传时间：	2025/12/10 9:27:07
中文题目：	A电力公司数据管理能力成熟度评估及提升策略研究
英文题目：	Research on the maturity assessment and improvement strategy of data management capabilities in A power company
指导老师：	樊振佳
中文关键字：	数据管理能力；DCMM 模型；PESTEL 分析；PDCA 循环
英文关键字：	Data Management Capabilities;DCMM model;SWOT analysis; PESTEL analysis;PDCA cycle
中文摘要：	当今世界正处于工业经济时代向数字经济时代迈进的重大变革期，数字技 术的加速迭代与融合创新，造成企业数据资源成指数级增长，数据已成为企业 核心资产之一，这一生产要素所需的管理能力是影响企业数字化转型的关键因 素。 A 电力公司（以下简称“A 电力公司”）作为国家电网有限公司内第一家 获评 DCMM4 级量化管理级评价的单位，数据管理能力的提升是增强企业核心 竞争力的关键手段。本文将基于 DCMM 数据管理能力成熟度评估模型，对 A 电力公司当前数据管理能力进行全面评估分析，发现薄弱项，给出适用性较强 的数据管理能力提升策略。 首先，本文针对 A 电力公司及其数据管理能力现状做简要分析，剖析公司 当前数据管理策略，建立数据管理能力成熟度评价指标体系。其次，通过问卷 调查法获取专家对指标体系的评价数据，利用层次分析法对各级指标进行权重 计算，结合模糊综合评价法分析各级指标的隶属度关系，进而确定当前 A 电力 公司数据管理能力成熟度所处等级。再次，结合专家对公司数据管理能力评价 问卷结果，运用 PESTEL 分析法诊断公司数据管理能力薄弱项，并且评估外部 宏观因素对公司数据管理能力成熟度提升的影响。最后，应用 PDCA 循环管理 工具进行数据管理能力成熟度提升策略制定，最终给出以“构建统一数据管理 体系，强化数据资源利用率”等优化建议，形成具有行业特色的数据管理能力 成熟度动态评估和持续改进的机制。
英文摘要：	The world is currently undergoing a significant transformation from an industrial economy to a digital economy era.The accelerated iteration and integration of digital technology have led to exponential growth in enterprise data resources，and the management capabilities required for data as a production factor are key factors affecting the digital transformation of enterprises. As the first unit within State Grid Corporation of China to receive the DCMM4 quantitative management level evaluation,A Power Supply Company believes that improving its data management capabilities is a key means of enhancing its core competitiveness.This thesis will comprehensively evaluate and analyze the current data management capabilities of Company A based on the DCMM model,identify weak areas,and provide highly applicable strategies for improving data management capabilities. Firstly，this thesis provides a brief analysis of Company A and its current data management capabilities，examining the company's current data management strategy and establishing an evaluation index system.Secondly, expert evaluation data on the indicator system was obtained through a questionnaire survey method,and the weights of each level of indicators were calculated using the AHP.Combined with the comprehensive fuzzy evaluation method,the membership relationship of each level of indicators was analyzed to determine the maturity level of A company's data management capability.Again,based on the results of the expert evaluation questionnaire on the company's data management capabilities,SWOT and PESTEL analysis methods were used to diagnose the two weak areas of the company's data strategy and data quality, and to evaluate the impact of external macro factors on the maturity of the company's data management capabilities.Finally,the PDCA cycle is applied to formulate improvement strategies, forming a dynamic evaluation and continuous improvement mechanism with industry characteristics.
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